Intelligent job matching system and method including negative filtration

ABSTRACT

A job searching and matching system and method is disclosed that gathers job seeker information in the form of job seeker parameters from one or more job seekers, gathers job information in the form of job parameters from prospective employers and/or recruiters, correlates the information with past job seeker behavior, parameters and behavior from other job seekers, and job parameters and, in response to a job seeker&#39;s query, provides matching job results based on common parameters between the job seeker and jobs along with suggested alternative jobs based on the co-relationships and based on ratings and preferences provided by the job seeker and provides negative filtration of undesirable jobs based on job seeker input and in response to queries from the system in order to efficiently and accurately accommodate job seeker perception. In addition, the system correlates employer/recruiter behavior information with past employer/recruiter behavior, parameters and information concerning other job seekers, which are candidates to the employer, and resume parameters, and, in response to a Employer&#39;s query, provides matching job seeker results based on common parameters between the job seeker resumes and jobs along with suggested alternative job seeker candidates based on the identified co-relationships and specifies job seekers to be eliminated from displayed results.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is related to U.S. patent application Ser. Nos.11/136,009 and 11/135,825, both filed on May 23, 2005, the disclosuresof which are incorporated herein by reference in their entirety. Thisapplication is also related to U.S. patent application Ser. No.11/441,997, entitled INTELLIGENT JOB MATCHING SYSTEM AND METHOD, filedon May 25, 2006, and U.S. patent application Ser. No. 11/441,638,entitled INTELLIGENT JOB MATCHING SYSTEM AND METHOD INCLUDING PREFERENCERANKING, filed May 25, 2006, both of which are co-owned by the assigneeof the present disclosure and are hereby incorporated herein byreference in their entirety.

BACKGROUND OF THE DISCLOSURE

1. Field of the Disclosure

The present disclosure relates to computer software. In particular, itrelates to a technique for enhancing job search results for both jobseekers looking for jobs and employer/recruiters looking for jobcandidates.

2. State of the Art

A challenge common to most companies seeking talented employees isfinding the best set of candidates for the position available. Onestandard practice among human resource departments is to create a jobdescription for each open position, then advertise the position alongwith the description. Recruiters and job seekers then have to review andanalyze these descriptions in order to determine a match between jobseekers and particular jobs.

A number of searching tools are available to a person searching on theInternet for the right job based on his or her skill set. Typicalsearching tools currently available require the job seeker to selectvarious criteria in the form of keywords, such as desired locations,types of jobs, desired compensation levels, etc. Similarly, theemployers provide, in addition to the job description, levels of skill,education, years of experience, etc. required to be considered for aparticular job. Searching tools then look up the seeker's keywords in adata base of job descriptions and return, or display those jobdescriptions that contain the job seeker's keywords.

However, available search tools still either often require the employerand the job seeker to each sift through a large number of so-calledsearch results or can return no search results at all if the criteriaprovided is too specific or narrow. It would be desirable, then, toprovide a matching search tool that more intelligently matches jobseekers to potential jobs and intelligently assists in narrowing a jobseeker's search for the right job. Such a search and matching tool isalso needed to assist an employer/recruiter in matching potential jobdescriptions to potential job seekers.

SUMMARY OF THE DISCLOSURE

A system and method for matching jobs or employment opportunities withjob seekers is disclosed which intelligently narrows search resultsbased on the job seeker's or employer/recruiter's search activity andpersonalized preferences. The system gathers a job seeker profile ofdesired and experiential information as job seeker parameters, from ajob seeker that accesses the system via a website. Similarly, the systemgathers job description information as job parameters from a prospectiveemploying entity such as an employer or recruiter, hereinafter termed an“employer/recruiter.” In addition, the system preferably can obtainfurther job opening information from other employment opportunitysources via a web crawler application so as to have as broad a base ofopportunities to present to a job seeker as possible. The system thencorrelates the available jobs, tracks all job seeker inquiries, andlooks for commonalities and correlations between job parameters,interests of job seekers, features of job seeker resumes, past actionsof the job seeker, specific preferences of the job seeker, and jobdescriptions to narrow in on a more accurate set of suggested jobs beingpresented to the job seeker each time the job seeker queries the systemfor matching potential jobs. In this way the system and method becomemore transparent and quickly become personalized to the preferences ofthe job seeker of the system.

Further, the system and method can be used by an employer/recruiter tosimilarly match prospective job seekers to an employer/recruiter's joband suggest other job seekers for consideration by theemployer/recruiter based on correlations between job parameters, jobseeker parameters, employer/recruiter actions, preferences, past actionsby the employer/recruiter, interactive queries between theemployer/recruiter and the system, and job seeker interest history inorder to iteratively narrow the search results to a more accurate set ofsuggestion job seekers being presented to the employer/recruiter.

An exemplary software system for matching a job seeker with a jobincludes a job seeker profile builder module connectable to a databaseoperable to generate job seeker profile parameters in response to jobseeker input. The system also includes a job profile builder moduleconnectable to the database that is operable to generate job profileparameters in response to employer/recruiter input, a matching modulefor matching the job seeker to a potential job through finding one ormore common parameters between job seeker parameters and job profileparameters and producing matching results, a correlation module operablyconnected to the matching module for determining a correlation betweenone of the common parameters and one or more selected parameters relatedto one of the job seeker, other job seekers and other jobs anddetermining relevance of the correlation to the matching results. Thesystem also includes a user interface accessible to one of the jobseeker and the employer/recruiter for displaying the matching resultsand alternative jobs. The system further includes, in the correlationmodule, a personalization module that the job seeker utilizes to modifythe correlations and resultant matches in accordance with user ratings,interactive search and/or matching rule modifications, and preferencesgleaned from interactions between the job seeker or employer/recruiteruser and queries within the correlation module.

An exemplary method for matching a job seeker with one or more of aplurality of jobs preferably includes building a job seeker profile ofjob seeker parameters in response to job seeker input, building a jobprofile of job parameters in response to employer input for each of theplurality of jobs, and, in response to a job seeker query, matching thejob seeker to a potential job through finding one or more commonparameters between job seeker parameters and job parameters andproducing matching results. The method also preferably includes trackingpopularity of one or more selected job parameters in the matchingresults based on activity from other job seekers, determining relevanceof alternative jobs to the matching results based on the popularity,interactively querying the job seeker to evaluate displayed matchingresults and provide responses, modifying correlations based on theresponses, determining relevance based on the responses, and iterativelydisplaying re-matching results and relevant alternative jobs forconsideration by the job seeker.

An exemplary method for matching a job seeker to a job or jobs includespermitting a job seeker to rate jobs previously presented to him/her indisplayed matching results and factoring in received ratings so thatsubsequent queries by the job seeker takes such ratings into account.Another method for matching a job seeker to a job or jobs includesengaging the job seeker in interactive evaluation to refine matchingrules and ranking user preferences established through ranking queriesprovided to the job seeker. These preferences are then utilized in thesystem such that listing generation for subsequent display of resultsprovided to the job seeker appears more focused and transparent to thejob seeker or employer/recruiter utilizing the system, thus permittingthe job seeker or employer/recruiter to more quickly focus on personallypreferred opportunities.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments are disclosed in the following detailed description.The disclosure will be better understood when consideration is given tothe following detailed description taken in conjunction with theaccompanying drawing figures wherein:

FIG. 1 shows an overall system view of an illustrative embodiment of ajob matching system incorporating features of the present disclosure.

FIGS. 2A and 2B are a high level process flow diagram for a simpleillustrative embodiment incorporating features of the presentdisclosure.

FIG. 3 is a process flow diagram for a matching module in anillustrative embodiment incorporating features of the presentdisclosure.

FIG. 4 is an exemplary web page screen that is preferably presented to ajob seeker in an illustrative embodiment incorporating features of thepresent disclosure.

FIG. 5 is an exemplary web page screen preferably presented to the jobseeker upon selecting a “View All my Jobs Recommended” in FIG. 4.

FIG. 6 is a simplified process flow diagram for any user, either a jobseeker or an employer/recruiter, utilizing an embodiment of the presentdisclosure.

FIG. 7 is an overall process flow diagram for a job search in anexemplary embodiment of the present disclosure in which the job seekerhas previously established an identification on the system shown in FIG.1.

FIG. 8 is a process flow diagram for a job search in an exemplaryembodiment of the present disclosure in which the job seeker hasidentification on an affiliated portal such as a web server, but not anestablished identification on the system.

FIG. 9 is a process flow diagram as in FIG. 8 in which the job seekerhas no prior identification on an affiliated portal but does have abrowser identifier such as a “cookie.”

FIG. 10 is a process flow diagram for an employer/recruiter inaccordance with an embodiment of the present disclosure.

FIG. 11 is an overall view of a simplified system in accordance withanother embodiment of the disclosure that utilizes only an affinitymodule in determination of match results.

FIG. 12 is a process flow diagram for the simplified system shown inFIG. 11.

FIG. 13 is an overall view of a more complex system in accordance withanother embodiment of the disclosure similar to that shown in FIG. 11that includes modules to illicit user input to enhance the matchingresults provided to the user.

FIG. 14 is a process flow diagram of the method using the system inaccordance with the embodiment shown in FIG. 13.

FIG. 15 is a screen shot of a user interface presented upon a userselecting similar jobs.

FIG. 16 is a screen shot of a user interface presented to a job seekerproviding search results.

FIG. 17 is a screen shot of a user interface presented to a job seekerto set ranking preferences in accordance with the disclosure.

DETAILED DESCRIPTION

Throughout this specification and in the drawing, like numerals will beutilized to identify like modules, operations and elements in theaccompanying drawing figures.

A block diagram of one exemplary embodiment of the job searcharchitecture software system 100 is shown in FIG. 1. The system 100includes a matching module 102, a database 104, and a correlation module106. As described herein, modules refer generally to functional elementsthat can be implemented in a centralized or distributed manner so thatfeatures or functions described in an exemplary manner as associatedwith one or more modules can be located or can take place or be carriedout in other modules or at other locations in the system.

The matching module 102 receives information and queries via a jobseeker interface module 108 and employer/recruiter interface module 110through accessing a web server 105 typically via the internet 101.Throughout this specification description, primarily an exemplary jobseeker will be used to describe system operations. However, this is notthe only use of the system 100. The system 100 preferably can also beused for example, in a reverse direction, by an employer/recruiter toevaluate candidate job seekers in a similar manner.

The web server 105 in turn communicates preferably through a search bank107 to the matching module 102 which draws from the correlation module106. The correlation module 106 incorporates a number of modules whichgather and catalog information from within the system 100 and othersources outside the system 100 to provide specific services to thematching module 102 for correlating information contained in thedatabase 104 and coordination with information from other sources.

The correlation module 106, for example, preferably includes one or moreof an affinity engine module 112, a location mapping module 114, a useractivity monitor module 116, a resume extraction module 118, a jobdescription extraction module 117, and a weight determination module119. The correlation module 106 can optionally also incorporate othermodules. The modules 112, 114, 116, 117, 118, 119, 121, and 123 aremerely exemplary of one embodiment illustrated. The correlation module106, in general, incorporates modules that provide information orcontain routines that look for relationships between various data anddraw inferences from the data that correlate with information provided,either directly or indirectly, from the job seeker and/or theemployer/recruiter.

The affinity engine module 112 within the correlation module 106generally examines combinations of informational parameters or data todetermine whether there are any correlations, i.e. affinities betweenany of the parameters. Such affinities preferably relate a job seeker toother job seekers based on, for example, a particular location, a job,skill set, job categories, spatial relationships, etc. Similarly, jobscan also be related to other jobs. In general, the affinity module 112is used to identify commonalities and trends between otherwise disparatedata. This information can then be utilized to identify alternative jobsto the job seeker or alternative job seeker candidates to anemployer/recruiter user of the system 100 that otherwise might bemissed.

The location mapping module 114 converts locations of jobs input byemployers/recruiters and desired work location input by job seekers into“geocodes,” specifically latitude and longitudinal coordinates such thatdistances between locations and relative spatial positions between jobsand job seekers can be easily manipulated and compared to determinerelative distances between locations. The information provided by thelocation mapping module 114 can be used by the matching module 102 orone of the other modules within the correlation module 106.

The user activity monitor module 116 tracks, for each job seeker, andeach employer/recruiter, his or her behavior, e.g., prior queries,choices, actions and interactions with the system 100 so as to be ableto draw correlations, e.g., inferences from such actions. For example, ajob seeker can apply for, or otherwise express an interest in one of anumber of suggested jobs. This “apply” fact is tracked for potential usein the affinity engine module 112 to infer other potential matches tooffer as suggested jobs. Note that throughout this specification, theterm “apply” is used. This term is synonymous and interchangeable withan expression of interest. Similarly, an employer/recruiter can examineresumes and indicate or otherwise express an interest in or contact forinterview one of a number of suggested job seekers for a particular job.This indicated interest fact, or behavior, is tracked in the useractivity monitor module 116, for use by the affinity engine module 112when the employer/recruiter next queries the system 100.

The job description extraction module 117 is a tool for extracting keyinformation from job descriptions, and other textual content, parameterssuch as job titles, skills required or recommended, prior experiencelevels, etc. There are a number of commercially available textextraction engines that can be used. For example, Resumix Extractor, nowmarketed by Yahoo Inc., described in U.S. Pat. No. 5,197,004 is one suchengine that can be incorporated into and utilized by this module 117.

Similarly, the resume extraction module 118 is a tool for extracting keyinformation from resumes, and other textual content, parameters such asjob titles, skills required or recommended, prior experience levels,etc. Again, there are a number of commercially available text extractionengines that can be used. For example, Resumix Extractor, now marketedby Yahoo Inc., described in U.S. Pat. No. 5,197,004 is one such enginethat can be incorporated into and utilized by this module 118.

The weight determination module 119 preferably incorporates an adaptivelearning engine and optionally can be tunable by the system operator,the job seeker, the employer/recruiter, or other system user. Thismodule 119 can essentially optimize weighting factors to be applied tothe various parameters in order to tune or more accurately hone in ondesired matched jobs or resumes based on input from the other modules inthe correlation module 106.

The Personalization module 121 examines what preferences the jobseekeror employer/recruiter has on his display screen to make inferences from.For a hypothetical example, if the jobseeker has stock ticker bannersoverlaying his/her window and New York weather site being monitored, thepersonalization module would provide this information so that the system100 might infer a tendency toward the northeast United States andpossibly a preference for the financial and business related industrypositions and factor that correlation into the suggestions that may bemade to the job seeker.

The personalization module 121 may, for example, include a ratingsmodule, a rules modification module and a negative filtration module,each designed to help the job seeker, or employer/recruiter refine andhone his or her preferred search criteria by interactively obtainingfrom the job seeker subjective information that might not otherwise beprovided. The rating module 125 provides a mechanism for the system 100to understand the relative value to the job seeker of recommendationsprovided and thus more accurately direct affinities that can be drawn.The rules modification module 127 may give the job seeker an opportunityto select or provide search criteria that he or she might not otherwiseintuitively provide that can help enhance the experience for the jobseeker. The negative filtration module 129 can similarly provide asimple mechanism for the job seeker to eliminate those recommendationsthat he or she views as outside the realm of interest. These modules allenhance the transparency of the system 100 to the job seeker oremployer/recruiter user so that each feels like the system iscustomizable to their needs. The personalization module 121 is shown asa dashed box since the enclosed modules 125, 127 and 129 may optionallybe separately provided or integrated into the personalization module121.

The Aggregate network data module 123 queries other sources on thenetwork to which the system 100 has access for any information relatedto the jobseeker. This module helps fill in details on the job seeker oremployer/recruiter from other available sources for relevant informationthat may be used to make correlations.

Job Seeker information is preferably developed in a Job Seeker ProfileBuilder module 200 within the job seeker module 108. Employer/recruiterjob information is preferably developed in a Job Profile Builder module202 within the Employer/Recruiter module 110. These two builder modules,shown in FIG. 2A, essentially provide tabular data as input to thematching module 102 while at the same time storing the profileinformational parameters in the database (DB) 104.

More particularly, the profile builder modules 200 and 202 feed theinformation obtained from the job seeker or the employer/recruiter, suchas the job seeker's city, state, login ID, etc, and employer/recruiterprovided job description information such as the job city, state, zipcode, company name, job title, etc into an Extraction, Translation andLoad (ETL) module 204 as shown in FIG. 2A. This ETL module 204optionally can require input and translation of the input data from theresume extraction module 118 and from the location mapping module 114 inorder to extract and load the information on the job and the job seekerproperly into the database 104 as a job seeker profile 206 and a jobprofile 208 as is shown in FIG. 2B. Once the profiles 206 and 208 aregenerated and stored in the database 104, the profiles are processed inthe matching module 102 to produce match results 210 into the matchingmodule 102.

In one embodiment, the job seeker profile builder module 200 queries ajob seeker, or the job seeker's person table, for some or all of thefollowing information and then constructs a job seeker profile 206.Exemplary entries in this profile 206 are described generally asfollows:

a. Location. This is the job seeker's desired location. Including thecity, state, country and zip code.

b. Proximity preference. This parameter is a number. The user will enterthis information or it can be imported from a mapping software product.

c. Industry. This information can be directly inputted by the job seekeror obtained from a person table previously generated by the job seekerand stored in the database 104.

d. Function. The function is the overall activity of the desired jobthat the job seeker is looking for. This information is obtained fromthe person table or directly inputted by the job seeker.

e. Title. This is the title of the desired job, if any, and ispreferably obtained from the job seeker directly or from his/her persontable, or it can be obtained from the job seeker's resume text throughan extraction program in the extraction module 118. In this case thetitle can correspond to the job seeker's most recent job title listed inhis/her resume text.

f. Past search criteria. For saved search, this information ispreferably stored in a job_agent table. For an ad-hoc search, the searchbank 107 where all data that is yet to be searched is queried. Thisincludes keywords used the job seeker has used in prior searches as wellas other indicators detailing prior behavior of the job seeker on thesystem 100.

g. Apply (expression of interest) history. The job seeker's prior jobapplication/interest history information is logged and updated in theuser activity monitor module 116 each time the job seeker applies for ajob utilizing this software system 100. This information is preferablyobtained from the job seeker's “jobs applied for” table, which is atable primarily containing the job seeker's resume ID and the appliedfor job ID and preferably includes a timestamp.

h. Click-throughs. This information comes from the user activity monitormodule 116 which tracks all activity of the job seeker on the system100, particularly sequential clicking activity, e.g. tracking action ofhow the job seeker got to the application stage, for example.

i. Resume ID. This is the same field as pindex in the person table. Thisis a unique identifier for a particular resume corresponding to aparticular job seeker. There can be several different resumes submittedby a single job seeker, depending on the one or more industries the jobseeker is interested in.

j. Login ID. This field has the job seeker's username. This field isalso put into the “match_result” table for fast access.

An exemplary Job seeker database table called “job_seeker_profile” isillustrated in Table 1 below.

TABLE 1 Column Name Description Nullable Resume_id Unique identifier fora N resume Latitude xxx.xxx Y Longitude yyy.yyy Y Proximity Number ofmiles within the Y desired location. Industry_id Unique identifier for aY industry Function_id Unique identifier for a job Y function Title_idUnique identifier for a job Y title. Extractor can be used to extractout the title. keyword Past search criteria saved Y by the user.Apply_history Apply history. This can be Y comma-separated job Ids. Alljobs that are “similar” to those in the apply history should be in thislist. Preferably obtained through the Activity monitoring module 116Click_throughs Job seeker click-throughs. This could be comma- separatedjob Ids. Preferably obtained through the Activity monitoring module 116login login id N resume Resume text Keyword_any Past search criteriasaved by the user. Match any of the words. Keyword_all Past searchcriteria saved by the user. Match all of the words. Keyword_phrase Pastsearch criteria saved by the user. Match the exact phrase. Keyword_nonePast search criteria saved by the user. Match none of the words. CityState Zip Province Country title This is the real title.Extracted_skills Extracted from the job seeker's resume using the Resumeextraction module 118.

Note that, to handle titles easily and simply, all real job titles arepreferably mapped to a set of predefined titles. In this table 1 above,the title column is the original title. The same approach is done forjob_profile 208 described below.

The Job Profile 208 preferably can include the following components.

a. Location. This is the job location. It is obtained from a job tablein the database 104 or from the employer/recruiter module 110.

b. Proximity preference. This parameter is a number representing thegeneral range of living locations within a reasonable distance from thejob location.

c. Industry. This information comes preferably from a job table in thedatabase or can be provided by the employer/recruiter.

d. Function. This info is preferably obtained from the job table in thedatabase 104 or can be provided by the employer/recruiter module 110.

e. Title. This is obtained from job table database or can be provided bythe employer/recruiter module 110.

f. Past search criteria. For previously saved searches, this informationis stored in an “agent_person” table in the database 104.

g. employer interest history. This information is either null or can beobtained from the user activity monitor module 116, or a Jobs Appliedfor table in the database 104.

h. Click-throughs. This can be obtained from the User activity monitormodule 116 which tracks the history of the actions taken by the user, ajob seeker or an employer/recruiter.

i. Job description analysis. This information can be provided by theEmployer/recruiter, previously stored in database 104 in a job table, orcan be obtained through the resume extraction module 118.

j. Job ID. This is the ID for this job.

k. User ID. This is the user account id.

The Job Profile builder 202 performs the same functions as the jobSeeker profile builder, in that the data is obtained from theemployer/recruiter to complete the job profile. Similarly, asophisticated keyword/phrase extractor such as “Resumix Extractor”marketed by Yahoo Inc. and described in U.S. Pat. No. 5,197,004 can beused to extract job titles from the job description and extract outskills for the extracted skills column.

An exemplary Job Profile table is shown below in Table 2.

TABLE 2 Column Name Description Nullable Job_id Unique identifier for ajob N Latitude Y Longitude Y Proximity Number of miles within the Ydesired location. Industry_id Unique identifier for a Y industryFunction_id Unique identifier for a job Y function Title_id Uniqueidentifier for a job Y title. Extractor can be used to extract out thetitle. Past_search Past search criteria saved by Y the user or ad-hocsearch performed by the user. Interest_history Employer interesthistory. Y This can be comma- separated resume IDs. All job seekerresumes that the employer/recruiter has expressed interest in can be inthis list. This is preferably obtained through the use of the useractivity monitoring module 116 Click_throughs Recruiter click-throughs.This could be comma- separated resume Ids. This is preferably obtainedthrough the use of the user activity monitoring module 116 user_id Ownerof the job Y login Employer/recruiter login id Y City State Zip ProvinceCountry Title The original title company The company nameExtracted_skills Extracted from job description using the jobdescription extraction module 117.

The job profile data and the job seeker profile data are then fed to thematching module 102. In the exemplary embodiment shown in FIG. 2, thematching module 102 draws information from one or more of the modules112-119, and, for example, from the affinity engine module 112 togenerate a set of matching results 210.

An embodiment of the matching algorithm 300 used in the matching module102 is shown in FIG. 3. In this exemplary embodiment, the matchingalgorithm 300 involves a two step approach. First, one or more of thelocation, industry, and title from the job seeker profile 206 and thelocation, industry, and title from prospective job profiles 208 areretrieved from the database 104 and evaluated in a course matchingoperation 301. To simplify location and proximity comparisons in thisfirst operation 301, locations preferably have been converted in thelocation mapping module 114, or alternatively directly by the job seekerinput or the employer/recruiter input, to geo-bound numbers so that whenlatitude and longitude are within the bound, the distance isapproximately within the proximity range desired. The operation 301provides a narrowing of the number of potential matches to those thathave an identity between corresponding locations, industries, and title.It is to be understood that other criteria can be utilized in the coarsematching operation 301 such as function instead of title, etc., but forthis example, identity between these three parameters will be used forillustration purposes only.

Given a job seeker (Iat, Ion, proximity, industryValue and titleValue),an exemplary SQL query to find all potential job matches is:

Sql = select * from job_profile j where   Abs(lat − j.latitude) <geoBound and abs(lon − j.longitude) <    geoBound and IndustryValue in(select value from industry_match   jm where j.industry_id =jm.industry_id) and titleValue   in (select value from title_match jmwhere j.title_id =   jm.title_id)

Note that, in this particular example, an exact match is required inoperation 301 so the query in the first step will be (given a jobseeker: Iat, Ion, proximity, industryId, titleId):

Sql = select * from job_profile j where   Abs(lat − j.latitude) <geoBound and abs(lon − j.longitude) <    geoBound and IndustryId =j.industry_id and TitleId = j.title_id

Control then transfers to matching operation 302.

In matching operation 302, a detailed match is made between the jobseeker profile 206 against this reduced list of potential jobs. Thisdetailed matching operation 302 in this exemplary embodiment involvesusing the following formula given a job seeker profile 206 and each jobprofile 208:S=LW*L+IW*I+FW*F+TW*T+SW*S+JW*J+AW*A+KW*K

Where:

S is the total matching score

LW is a weight given to the location parameter.

L is the location matching score 312.

IW is a weight given to the industry factor.

I is the industry matching score 314.

FW is a weight given to the job function factor.

F is the job function factor 316.

TW is a weight given to the title parameter.

T is the title matching score 318.

SW is a weight given to the past search factor.

S is a past search matching score 320.

JW is a weight given to the apply history for the job seeker andclick-throughs parameter.

J is the apply history and click-throughs matching score 322.

AW is a weight given to the resume/job description text matchingparameter.

A is the resume/job description matching score 324.

KW is a weight given to the skill set matching score.

K is the skill set matching score 321.

Each of the weights 304 that are used is a value that initially is oneand can be varied based on user prior activity history, determined inactivity monitoring module 116 or can be tunable by the job seeker oremployer/recruiter user or system operator, whoever is using the system100 at the particular time using the weight determination module 119shown in FIG. 1.

Each of the matching scores 312-324 is preferably determined in aparticular manner exemplified by the following descriptions of anexemplary embodiment. The location matching score “L” (312) iscalculated according to the following formula: L=1−D/P where D is thedistance between the desired location by the jobseeker and the actualjob location and P is the Proximity parameter given in the job seeker orjob profile tables. When L is negative, the location is out of range,which means they do not match. The score is linearly reduced with thedistance. One is the highest score, when the distance is zero.

The Industry matching score 314 is calculated according to a matrix inwhich I=IndustryMatchMatrix (DesiredIndustry, ActualIndustry). Anexample is given using the following Table 4 below.

TABLE 4 Banking Finance Software Eng. Prog. Analyst Banking 1 0.5 0 0Finance 0.5 1 0 0 Software Eng. 0 0 1 0.6 Prog. Analyst 0 0 0.6 1

In Table 4, assume for a particular match scenario between a job seekerand a job is that the desired industry is banking and the actual jobindustry is also banking. In this case, the industry match score wouldbe 1. However, if the desired industry is a programmer analyst and theindustry is banking, the industry match score would be zero. Similarly,if the job seeker's desired industry is a software engineer and the jobindustry is programmer analyst, the industry match score would beweighted more toward a match, thus 0.6 would apply because there arenumerous similarities between these industries. The actual industrymatching table is many orders of magnitude larger than Table 4, but thephilosophy behind table development is the same.

The function matching score “F” (316) and the Title matching score “T”(318) are preferably determined utilizing matrix tables similar indesign to that of Table 4 above, but it will be recognized thattechniques other than tabular matrices can be employed.

The past search matching score “S” (320) may or may not apply. If a jobseeker has saved searches, then this term will apply. This score S (320)is determined by S=Number of matching terms/minimum of: number of termsfor the job seeker or number of terms for the employer/recruiter. Thus,if only the job seeker has a saved search, then if keywords are present,search keywords against the job description. Then S=number of matchingterms/number of terms.

If only the employer/recruiter has a saved search, then a search is madeof keywords in the resume text and S=number of matching terms/number ofterms in the job seeker resume text.

The apply history and click-through matching score 322 is generallycalculated using the affinity engine 112 and the user activitymonitoring module 116. The affinity engine generates an affinity fileusing data from a “jobs applied for” (expression of interest) file asdescribed in more detail below with reference to Table 5. This filetracks all jobs for which the job seeker has applied for or otherwiseexpressed an interest in. Note that a “click-through,” in this exemplaryembodiment being described, is determined in the user activitymonitoring module 116 and tracks every job seeker action, such as when ajob seeker “clicks through” from one screen to another, selectssomething to view, enters information, or applies to a job. In the caseof an employer/recruiter user, the apply history and click throughmatching score 322 is really a candidate job seeker interest history andclick through matching score. In this latter case, the actions of theemployer/recruiter user are tracked and employer/recruiter's indicatedinterest in a candidate job seeker is logged in the activity monitormodule 116. Thus the click through is a path history of how theemployer/recruiter reached the conclusion to conduct an interview orpass on a resume of interest to the appropriate personnel manager. Thisinformation is tracked so that his/her reasoning and preferences can bededuced.

The affinity module preferably can utilize an affinity engine such as isdescribed in U.S. Pat. No. 6,873,996, assigned to the assignee of thepresent disclosure and hereby incorporated by reference in its entirety.The affinity engine operation in affinity module 112 to determine thematching score 322 can be simply understood with reference to an exampleset forth in Table 5 below, and the description thereafter.

TABLE 5 Job Seeker Applied for Job P1 J1 P2 J2 P3 J1 P4 J2 P5 J1 P6 J1P7 J2 P8 J1 P9 J2 P2 J1 P4 J1 P6 J2 P8 J2  P10 J2  P11 J2 P1 J3 P1 J4 P2J3

a. Job1 to job2 affinity is defined as follows: a=J12/J1, where J12 isthe number of applicants who applied for both job1 and job2, J1 is thenumber of applicants who applied for job1.

b. Job1 to Job2 normalized affinity is defined as follows: n=a/(J2/N),where a is Job1 to Job2 affinity, J2 is the number of applicants whoapplied for Job2, N is the total applicants. Note that N is a commonfactor, so it can be taken out.

The score=# of multiple applies “m” divided by J1 applies times J2applies. Thus, In this Table 5, job seekers P1, P2, P3, P4, P5, P6 andP8 each applied for the job identified as “J1.” Thus the affinity for J1is a Total number: 7. Job seekers P2, P4, P6, P7, P9, P8, P10 and P11applied for J2. Total number: 8. Note that job seekers P2, P4, P6 and P8applied for both jobs J1 and J2. Total number: 4.

Therefore J2 is a recommendation for J1 with a score of 4/(7×8)=0.07.

J1 is a recommendation for J2 with a score of 4/(8×7)=0.07.

J3 is a recommendation for J1 with a score of 1/(1×7)=0.14.

This same exemplary apply history can also generate affinities for jobseeker (candidates) so that system 100 can make recommendations foremployers/recruiters. For example, P1 applied for J1, J3 and J4. P2applied for J1, J2 and J3. P1 and P2 both applied for J1 and J3. So P1is a recommendation for P2 with a score of 2/(3×3)=0.33.

Each of the match scores is calculated in operation 302. As discussedabove weights can also be factored into each individual score fromoperation 304. The affinity engine module 112 is used, as an example, inthe apply history score determination. As mentioned above, in thisparticular example, the title match score determination operation 306,the industry match score determination operation 310 and the locationmatch score are required to match at a value of one.

The results of the match operation are stored in the database 104 in amatch_result table 326, an example of which is shown in such as Table 6below.

TABLE 6 Column Name Description Nullable Resume_id Resume ID N Job_idJob ID N Member_id Member ID N SCORE Matching score N CTIME Created timestamp N SHOWN_TO_CANDIDATE This job is N (Two valid displayed on thevalues: Y, N. job seeker's home Default to N.) pageCANDIDATE_CLICKED_TIME The time when the Y candidate clicked this link.SHOWN_TO_MEMBER This resume is N (Two valid displayed on the values: Y,N. member's home Default to N.) page. MEMBER_CLICKED_TIME The time whenthe Y member clicked this link. Member_login Y Job_seeker_login NIndustry: create an industry table as follows: Industry_id Number NIndustry_name varchar N Industry: create a function table as follows:function_id Number N function_name varchar N Industry: create a titletable as follows: titley_id Number N title_name varchar N

When a job seeker, or an employer/recruiter, logs in to the system 100,all jobs he/she ever applied for are retrieved from database 104,ordered by date. In the case of the employer/recruiter, all candidatejob seekers marked by the employer/recruiter as being of interest to theemployer/recruiter are retrieved in a similar manner. The correlationmodule 106 then is utilized in conjunction with the matching module 102to identify potential other jobs (or other candidates) based on his/herapplied for history (or employer interest history).

A screen shot 400 of an exemplary job seeker web page is shown in FIG.4. In FIG. 4, the job seeker, in this case an individual who has signedon previously and has applied for jobs via the system 100 which havebeen saved, is presented with other jobs 402 that he might be interestedin. If the job seeker then clicks on the “View All My JobRecommendations” 404, the screen 500 shown in FIG. 5 is presented. Herethere are eight jobs 502 presented to the job seeker along with a seriesof potential selections 504 for him to choose those positions thathe/she is not interested in. When the job seeker places a check 506 inone of these boxes as shown, this action is tracked and saved in theuser activity monitor module 116. This job and its associated parameterswill no longer be considered in the matching module 102, although theparameters will be considered when handled in the user activity monitormodule 116 in future search results. No jobs marked “not interested” bya job seeker will show to the job seeker in subsequent queries. Also,all applied jobs and saved jobs will not be recommended again to the jobseeker. A new column called “jobsnotinterestedids” is added to the userprofile table to store all the job ids that the user is not interestedin.

Similarly, if an employer/recruiter checks a “not interested” block fora particular job seeker candidate, in a corresponding screen, thatparticular job seeker will no longer show to the employer/recruiter inany subsequent queries. A corresponding column called“candidatesnotinterestedids” would be added to the employer/recruiterprofile table to store all the job seeker IDs that the user is notinterested in.

Referring now to FIG. 6, a simplified general process flow diagram 600of one sequence of operations that occur when a job seeker oremployer/recruiter signs on to the system 100. In operation 602 the jobseeker is presented with, and looks at an exemplary job description.Control then transfers to query operation 604. Here the user is askedwhether he likes this job and therefore would like to see more jobdescriptions like this one. If the user clicks on “yes” or “show me morelike this one” etc., then control transfers to operation 606 and theuser sees a different screen with a series of different but similar jobdescriptions. On the other hand, if the user clicks or selects “No,”then control transfers to return operation 608 and control returns tothe calling operation, whatever it might have been.

Specifically for job seekers, several scenarios are shown in FIGS. 7through 9. FIG. 10 provides an exemplary flow diagram for anemployer/recruiter.

FIG. 7 shows a sequence of operations 700 when a job seeker 702 accessesthe system 100 and the job seeker is a prior system user with his ownlogin ID. The job seeker 702 enters his ID code in operation 704 to logonto the system 100. When he does so, control transfers to operation706. In operation 706, the job seeker's user profile 206 is retrievedfrom the database 104. Control then transfers to operation 708, wherethe system 100 searches available jobs in module 102 as described abovewith reference to FIG. 3, and displays the matching results to the jobseeker, on a screen similar to that shown in FIG. 4. Control thentransfers to operation 710 where the system 100 awaits the job seeker tochoose whether to apply for a displayed job. If the job seeker choosesnot to apply for a job, control transfers to return operation 712. Onthe other hand, if the user chooses to apply for one of the jobs, theapply history for the job seeker is updated in the user activitymonitoring module 116, and control transfers to operation 714.

In operation 714, since the job seeker has now applied for one of thedisplayed jobs, a new search through the sequence 300 shown in FIG. 3 isperformed, with the updated apply history and click-through informationprovided as a result of the job seeker's actions. Control then returnsto query operation 710, in which the new search results are displayed tothe job seeker 702. Again, the job seeker 702 is given the opportunityto apply for one of the displayed jobs and, if he/she does so, controlagain passes to operation 714, the matching search sequence 300 repeats,and then back to query operation 710. This iterative process repeatsuntil the job seeker chooses not to apply for one of the displayed jobs,at which point control transfers to return operation 712.

FIG. 8 shows a sequence of operations 800 when a job seeker 802 accessesthe system 100 and the job seeker is not a prior system 100 user butdoes have a login ID for the web system on which system 100 resides.Therefore there is some basic information on the job seeker in thedatabase 104 which can be utilized. The job seeker 802 enters his IDcode in operation 804 to log onto the system 100. When he does so,control transfers to operation 806. In operation 806, the job seeker'savailable profile is retrieved from the database 104. This profile willnecessarily be more limited than the corresponding profile 206 for theprior user 702.

Control then transfers to operation 808, where the system 100 matchesavailable jobs via module 102 as described above with reference to FIG.3, with the available profile and displays the matching results to thejob seeker 802, again on a screen similar to that shown in FIG. 4.Control then transfers to query operation 810. Query operation 801 ofthe system 100 permits the job seeker 802 to choose whether to addanother search parameter. If the job seeker 802 chooses not to addanother search parameter or request a search with different parameters,control transfers to return operation 812. On the other hand, if the jobseeker 802 adds or changes a parameter, the click-through history forthe job seeker is updated in the user activity monitoring module 116,and control transfers to operation 814.

In operation 814, since the job seeker has now requested a modifiedsearch by adding or changing a parameter, a new search through thematching sequence 300 shown in FIG. 3 is performed, with the updatedclick-through information provided as a result of the job seeker'sactions. Control then returns to query operation 810, in which the newsearch results are displayed to the job seeker 802. Again, the jobseeker 802 is given the opportunity to modify parameters for anothersearch, and, if he/she does so, control again passes to operation 814,the matching search sequence 300 repeats, and then back to queryoperation 810. This iterative process repeats until the job seekerchooses not to apply for one of the displayed jobs, at which pointcontrol transfers to return operation 812 where the job seeker cncontinue with another search. The principal difference between theexemplary sequences shown in FIGS. 7 and 8 is that the job seeker 802 isnot given the opportunity to actually apply for a displayed job throughthe system 100 until he/she becomes a recognized job seeker as jobseeker 702 with a properly generated job seeker profile 206. The jobseeker will not be able to be shown a best match until such a profile206 is generated.

FIG. 9 shows an exemplary sequence of operations 900 when a job seeker902 accesses the system 100 and the job seeker 902 has no prior historyat all either with the system 100 or with a portal such as the webserver 105 carrying system 100. Here the job seeker 902 likely has noknown ID. The job seeker 902 therefore enters as a visitor in operation904 to log onto the system 100. When he does so, control transfers toquery operation 906. In query operation 906, the job seeker's browser IDis identified using cookies obtained from his browser software todetermine whether there are any previous searches for this user. If not,control transfers to query operation 910. However, if there is aprevious search retrieved from the database 104, control then transfersto operation 908, where the system 100 searches available jobs in module102 as described above with reference to FIG. 3, based on the storedprior search results, and displays the matching results to the jobseeker 902, again on a screen similar to that shown in FIG. 4. Controlthen transfers to operation 910 where the system 100 awaits the jobseeker 902 to choose whether to conduct a search. If the job seekerchooses not to search, control transfers to return operation 912. On theother hand, if the user chooses to conduct a search, the history for thejob seeker 902 is updated, if any from previous searches, in the useractivity monitoring module 116, and control transfers to operation 914.

In operation 914, since the job seeker has requested a search, a newsearch through the matching sequence 300 shown in FIG. 3 is performed,with the updated click-through information provided as a result of thejob seeker's actions. Control then returns to query operation 910, inwhich the new matching results are displayed to the job seeker 902.Again, the job seeker 902 is given the opportunity to modify parametersand request a modified search for jobs and, if he/she does so, controlagain passes to operation 914, the matching search sequence 300 repeatswith the modified parameters, and then control passes back to the queryoperation 910. This iterative process repeats until the job seeker 902chooses not to modify the search so as to modify the match, at whichpoint control transfers to return operation 912.

FIG. 10 shows a sequence of operations 1000 when an employer/recruiter1002 accesses the system 100 and the employer recruiter 1002 is a priorsystem user with his own employer login ID. The employer/recruiter 1002enters his ID code in operation 1004 to log onto the system 100. When hedoes so, control transfers to operation 1006. In operation 1006, theemployer/recruiter's user profile 206 is retrieved from the database104. Control then transfers to query operation 1008. Here, the questionis asked whether the employer/recruiter wishes to retrieve and examine aparticular job folder containing jobs he/she has already loaded profilesof and saved. If not, control transfers to return operation 1010. if theemployer/recruiter selects a job folder, answering yes in queryoperation 1008, control transfers to operation 1012.

In control operation 1012 the system 100 searches all the resumes in thedatabase 104 using the recruiter profile and the job profile on file inthe job folder, in matching module 102 as described above with referenceto FIG. 3, and displays the matching results to the employer/recruiter1002, on a screen similar to that shown in FIG. 4, except set up for theemployer/recruiter 1002. Control then passes to query operation 1014.

In query operation 1014, the question is asked of the employer/recruiterwhether he/she is interested in a particular displayed resume. If so,then control transfers to operation 1016 in which the selected resume isdisplayed for the employer 1002. If no resume is chosen for display,however, control returns to query operation 1008, where theemployer/recruiter is again asked to go to a job folder, perhaps thistime to a different job folder.

Once the employer/recruiter views a resume in operation 1016, controltransfers to query operation 1018. Query operation 1018 asks whether therecruiter wants to se other resumes similar to the one shown. If theanswer is yes, control transfers to operation 1020. In query operation1020, the employer/recruiter is asked whether the next search of similarresumes should included additional predefined options. If so, controltransfers to operation 1022 where the employer/recruiter inputs theselected options or qualifications to more narrowly define the search.Control then transfers to operation 1024 where the resumes are againsearched with the new input from the predefined set of options, orsimply with the click-through history added from the just completedsearch and the search of resumes is again performed. The results of thisresearch are displayed to the employer/recruiter in operation 1012 againas potential job seeker candidates instead of potential jobs. Controlthen transfers again to query operation 1014. This iterative processthrough operations 1012 through operation 1024 is repeated until theemployer/recruiter 1002 returns a negative answer in operation 1014 andthen in operation 1008 such that control transfers to return operation1010.

Another simplified embodiment of the system in accordance with thepresent disclosure is illustrated in FIGS. 11 and 12. In thisembodiment, the system 1100 includes a matching module 1102, a database1104, and a correlation module 1106. The matching module 1102 receivesinformation and queries via a job seeker interface module 1108 andemployer/recruiter interface module 1110 through accessing a portal suchas a web server 1105 typically via the internet 1101.

Throughout this description, primarily an exemplary job seeker will beused to describe system operations. However, this is not the only use ofthe system 1100. The system 1100 can also be used for example, in areverse direction, by an employer/recruiter to evaluate candidate jobseekers in a similar manner.

The web server 1105 in turn communicates preferably through a searchbank 1107 to the matching module 1102 which draws from the correlationmodule 1106, although the matching module 1102 can communicate directlyto and through the web server 1105 to the job seeker module 1108 or theemployer/recruiter module 1110. The correlation module 1106 in thisembodiment is limited in its content to an affinity engine module 1112and a user activity monitor Module 1116. The affinity module 1112provides information and contains routines that look for relationshipsbetween job data and job seeker data and draw inferences from the datathat correlate with information provided, either directly or indirectly,from the job seeker and/or the employer/recruiter.

The affinity engine module 1112 within the correlation module 1106generally examines combinations of informational parameters or data todetermine whether there are any correlations, i.e. affinities betweenany of the parameters. Such affinities can relate a job seeker to otherjob seekers based on, for example, a particular location, a job, skillset, job categories, spatial relationships, etc. Similarly, jobs canalso be related to other jobs. In general, the affinity module 1112 isused to identify commonalities and trends between otherwise disparatedata. This information can then be utilized to identify alternative jobsto the job seeker or alternative job seeker candidates to anemployer/recruiter user of the system 1100 that otherwise might bemissed.

The affinity module again preferably can utilize an affinity engine suchas is described in U.S. Pat. No. 6,873,996, assigned to the assignee ofthe present disclosure and hereby incorporated by reference in itsentirety. The affinity engine operation in affinity module 1112 todetermine the matching score 322 as set forth in FIG. 3 above, can besimply understood with reference to an example set forth in Table 5discussed in detail above.

The user activity monitor module 1116 tracks, for each job seeker, andeach employer/recruiter, his or her prior queries, choices, actions andinteractions with the system 1100 so as to be able to draw correlations,e.g., inferences from such actions. For example, a job seeker can applyfor one of a number of suggested jobs. This “apply” fact is tracked forpotential use in the affinity engine module 1112 to infer otherpotential matches to offer as suggested jobs. Similarly, anemployer/recruiter can examine resumes and indicate an interest in orcontact for interview one of a number of suggested job seekers for aparticular job. This indicated interest fact is tracked in the useractivity monitor module 1116, for use by the affinity engine module 1112when the employer/recruiter next queries the system 1100.

In this simplified embodiment 1100, the matching is limited in severaldistinct ways. First, the job location, the job title, and the industryare all identical between the jobs and the job seeker 1102 and thusthere is a one to one match on each of these parameters. Second, thematching is only performed utilizing apply history (prior applied forjobs). As mentioned above, in this particular example, the title matchscore determination operation 306, the industry match scoredetermination operation 310 and the location match score, all referringto FIG. 3, are required to match at a value of one. The results of thematch operation are stored in the database 1104.

Third, the affinity module 1112 in this simplified embodiment looks onlyat other job seekers and other jobs those job seekers have applied for,as is particularly shown in the example set forth in Table 5.

FIG. 12 shows a sequence of operations 1200 when a job seeker 1202accesses the simplified system 1100 and the job seeker is a prior systemuser with his own Login ID. The job seeker 1202 enters his ID code inoperation 1204 to log onto the system 1100. When he does so, controltransfers to operation 1206. In operation 1206, the job seeker's userprofile 206 is retrieved from the database 1104. This previously savedprofile 206 will contain any records of jobs that the job seekerpreviously applied for.

If such previously applied for jobs are found, control transfers tooperation 1208 where the system 1100 searches and matches available jobsin module 1102 as described above with reference to FIG. 3, and thendisplays the matching results to the job seeker 1202, on a screensimilar to that shown in FIG. 4. Control then transfers to operation1214 where the system 1100 permits the job seeker to choose to apply fora newly displayed job. If the job seeker chooses not to apply for one ofthe displayed jobs, control transfers to query operation 1210. On theother hand, if the user chooses to apply for one of the jobs, the applyhistory for the job seeker is updated in the user activity monitoringmodule 116, and control transfers to operation 1216.

In operation 1216, since the job seeker has now applied for one of thedisplayed jobs, a new search and matching operation, through thesequence 300 shown in FIG. 3, is performed with the updated applyhistory and click-through information provided as a result of the jobseeker's actions. The results of this match are displayed asrecommendations to the job seeker 1202. Control then returns to queryoperation 1214. Again, the job seeker 1202 is given the opportunity toapply for one of the newly displayed jobs and, if he/she does so,control again passes to operation 1216, the matching search sequence 300repeats, and then back to query operation 1214. This iterative processrepeats until the job seeker chooses not to apply for one of thedisplayed jobs, at which point control transfers to operation 1210.

When control transfers to query operation 1210, either from operation1214 as just described, or initially from query operation 1206, if thestored job seeker profile 206 contains no previous applied for jobs, thejob seeker 1202 is permitted to conduct a new search for jobs. In thiscase, perhaps the job seeker can provide different input parameters forthe job search desired, such as a different location, title, etc. Ifsuch a new search is requested, control transfers to operation 1212where the search is conducted and matching results are displayed aspotential jobs. Control then passes to query operation 1214 as abovedescribed.

On the other hand, if the job seeker 1202 does not want to performanother job search at this time, the job seeker's job profile 206 isupdated and stored, and control passes to return operation 1218 in whichthe current process 1200 terminates. The next time the job seeker 1202logs into the system 1100, the above described process again begins, butthis time with updated information in the job seeker's profile 206 basedon the previously applied for jobs and correlations determined in theaffinity module 112 described above.

Another more complex embodiment of a system in accordance with thepresent disclosure is illustrated in FIGS. 13 through 17. Thisembodiment provides improved functionality and usability for the user,whether job seeker or employer/recruiter, in order to more efficientlyand transparently narrow search results in a manner useful to the user.Throughout the description of this embodiment, an exemplary job seekerwill be used primarily to describe system operations. However, this isnot the only use of the system 1300. The system 1300 can also be usedfor example, in a reverse direction, by an employer/recruiter toevaluate candidate job seekers in a similar manner.

In this embodiment, the system 1300 includes a matching module 1302, adatabase 1304, and a correlation module 1306 as in the embodimentsdescribed above. The matching module 1302 receives information andqueries via a job seeker interface module 108 and employer/recruiterinterface module 110 through accessing a portal such as a web server1305 typically via the internet 101.

The web server 1305 in turn communicates preferably through a searchbank 1307 to the matching module 1302 which draws from the correlationmodule 1106, although the matching module 1302 can communicate directlyto and through the web server 1305 to the job seeker module 108 or theemployer/recruiter module 110. The correlation module 1306 in thisembodiment is not limited in its content to an affinity engine module1312 and a user activity monitor Module 1316. The affinity module 1312provides information and contains routines that look for relationshipsbetween job data and job seeker data and draw inferences from the datathat correlate with information provided, either directly or indirectly,from the job seeker and/or the employer/recruiter.

The affinity engine module 1312 within the correlation module 1306generally examines combinations of informational parameters or data todetermine whether there are any correlations, i.e. affinities betweenany of the parameters. Such affinities can relate a job seeker to otherjob seekers based on, for example, a particular location, a job, skillset, job categories, spatial relationships, etc. Similarly, jobs canalso be related to other jobs. In general, the affinity module 1312 isused to identify commonalities and trends between otherwise disparatedata. This information can then be utilized to identify alternative jobsto the job seeker or alternative job seeker candidates to anemployer/recruiter user of the system 1300 that otherwise might bemissed.

The affinity module again preferably can utilize an affinity engine suchas is described in U.S. Pat. No. 6,873,996, assigned to the assignee ofthe present disclosure and hereby incorporated by reference in itsentirety. The affinity engine operation in affinity module 1312 todetermine the matching score 322 as set forth in FIG. 3 above, can besimply understood with reference to an example set forth in Table 5discussed in detail above.

The user activity monitor module 1314 tracks, for each job seeker, andeach employer/recruiter, his or her prior queries, choices, actions andinteractions with the system 1300 so as to be able to draw correlations,e.g., inferences from such actions. For example, a job seeker can applyfor one of a number of suggested jobs. This “apply” fact is tracked forpotential use in the affinity engine module 1312 to infer otherpotential matches to offer as suggested jobs. Similarly, anemployer/recruiter can examine resumes and indicate an interest in orcontact for interview one of a number of suggested job seekers for aparticular job. This indicated interest fact is tracked in the useractivity monitor module 1314, for use by the affinity engine module 1312when the employer/recruiter next queries the system 1300.

The correlation module 1306 in this embodiment also includes a ratingsmodule 1316, a filtering module 1318, and a preference ranking module1320, all designed to assist a user, whether she be job seeker oremployer/recruiter, by personalizing the system to make it moretransparent and effective for the user.

In this embodiment 1300, the functionality of the matching is lesslimited in several distinct ways from that of embodiment 1100 describedabove. First, the job location, the job title, and the industry maydiffer between the jobs and the job seeker 102 and thus there is notnecessarily a one to one match on each of these parameters. Second, thematching is performed utilizing apply history (prior applied for jobs)as well as several input parameters received from interaction from theuser. As mentioned above, in the previous example, the title match scoredetermination operation 306, the industry match score determinationoperation 310 and the location match score, all referring to FIG. 3, maymatch at a value of one. The results of the match operation are storedin the database 1304.

Second, the job ratings module 1316, the filtration module 1318, and theperformance ranking module 1320 all contribute to the functionality ofthe user activity monitor module 1314.

Third, the affinity module 1312 in this embodiment looks at other jobseekers and other jobs those job seekers have applied for, as isparticularly shown in the example set forth in Table 5 and, in addition,evaluates user input received from a ratings module 1316, a filteringmodule 1318, and a preference ranking module 1320. Each of these modulesprovides input to the affinity module 1312, and, in turn, the matchingmodule 1302, in response to interaction between the Job Seeker and thesystem 1300 as illustrated in the accompanying flow diagram of FIG. 14below. This interaction between the system and the job seeker provides apersonalized aspect to the system 1300 that is absent from the systemshown in FIG. 11. Hence this embodiment 1300 gives the job seeker anenhanced transparency experience that efficiently leads to the type ofresults that he or she may be searching for.

For example, an additional database called “LDB” may be incorporatedinto database 1304. This LDB database provides preference informationdetermined in response to queries made to the user in the user'sprofile. These preferences may include: location_preference,type_preference, title_preference, industry_preference,experience_preference. Each field has the same data structure:Field value=record^Arecord^Arecord^Arecord . . .Record=value^Bimportance_score . . . .

Where ^A and ^B are delimiters. ^A separates records and ^B separatesfields within a record. This information may be stored in other datastructures and/or data storages such as an Oracle database. For example,location_preference field could have the following value:Sunnyvale-CA-USA^B5^ANew York-NY-USA^B-5^AChicago-IL-USA^B-0Here 5 applied jobs have the location Sunnyvale, Calif., USA and none ofthe “not-interested-jobs” has this location. 5 “not-interested-jobs”have the New York location and none of the applied jobs is located inNew York. The significance of −0 for Chicago is that the user explicitlysaid he/she did not like Chicago. If it was “0” for Chicago, then itwould mean that the user explicitly said he/she liked Chicago.

The following is an example for the type_preference field:PERM^B6^ACONT^B-5^ATEMP-0

Similarly, for title, a standard set of titles may be defined along withuser specified not-interested titles. For industries, preferablystandard industry codes are used. For company names, variations of namesare encompassed. For experience level, a numerical span of years isutilized.

As an example of information collection from the user, whether jobseeker 108 or employer/recruiter 110, the following description isexemplary. When a job seeker 108 clicks “No Interest” on a displayedjob, a popup small window may be displayed asking the job seeker 108what he/she does not like about this job, with a series of predefineddescriptions provided. For example, “I don't like the title”, “I don'tlike the location”, I don't like the industry”, “I don't like thecompany” may be used. If the user does or does not check any of thesedescriptions, that fact is saved as a user preference for use in theuser activity module 1314, the affinity module 1312, and the matchingmodule 1302.

When a user expresses no interest in a particular displayed job, thesystem 1300 learns from that. As mentioned previously, attributes aredefined that enable the job seeker to focus on such as “title”,“location”, “industry”, “company”, “type of job”. These attributes arecombined with saved searches, applied for jobs, and not-interested jobs.Lists of predefined attributes for applied for jobs and disliked jobsare compared in order to cull common attribute values to create two hashmaps. One is a positive map that contains any attribute-value pairs thatare in the applied list but not in the disliked list. The other is anegative map that contains any attribute-value pairs that are in thedisliked list but not in the applied list. The two maps can then be thebasis for preference ranking analysis.

Positive ranking utilizes commonality of attribute-value pair to rankrecommended jobs. For example, if location_Sunnyvale is the most commonpair among the applied for jobs, recommendation of jobs with location“Sunnyvale” should be presented to the job seeker first, i.e., on thetop.

Negative ranking is similarly accomplished using commonality ofattribute-value pairs to filter jobs. For example, if location_Sunnyvaleis the most common pair in the disliked jobs list, then the system 1300may filter out all jobs with location “Sunnyvale”, or at least placethem last in the presentation to the job seeker 108.

An example of a user preference ranking setting screen 1700 is shown inFIG. 17. Each of the major categories, location, title, industry, jobtype, company, and experience level is shown along with a weightingfactor 1702, a most preferred parameter 1704, and a least preferredparameter 1706. As an example, note that location for this user isweighted at 30%, while all of the other parameters are weighted less. Ifthe job seeker now decides that he/she wants to zero in on the title ofthe job rather than its location, she could change the title weight to30% while reducing one of the other categories. Note that the sum of theweights must equal 100%. Thus if the location is the most importantcategory, and ALL other criteria are of no significance, one could evenweight Location as 100% and all others as 0%. The jobs displayed wouldthen all be ranked first according to the most preferred location toleast preferred, with no weight being given to title, industry, type,company or experience level.

As a job seeker utilizes the system 1300, at any time he or she mayaccess her preferences pages. The ranking settings page shows each ofthe major categories and provides the user with an opportunity to changeeach of the three parameters associated with each category. The rankingsettings govern how the system displays results to the job seeker 108 oremployer/recruiter 110. The preference ranking module 1320, filtrationmodule 1318 and ratings module may be utilized alone or together toprovide a more transparent and personalized job search system to theuser than the simplified version 1100 described with reference to FIG.11 above. In this more advanced system 1300, when the job seeker 108first signs in, he/she may be directed to the preferences screen wherehe or she is presented with explanations as to how the user can enhancetheir search results. In addition, each time a search is made, theinteractions, preferences and results are incorporated by the affinitymodule 1312 and user activity monitor module 1314 in order tocontinually refine the strategy for search and presentation of searchresults to the job seeker 108 or employer/recruiter 110.

FIG. 14 shows an enhanced sequence of operations 1400 when a job seeker1402 accesses the system 1300 and the job seeker is a prior system userwith his own Login ID. The job seeker 1402 enters his ID code inoperation 1404 to log onto the system 1300. When he does so, controltransfers to operation 1406. In operation 1406, the job seeker's userprofile 206 is retrieved from the database 1304. This previously savedprofile 206 will contain any records of jobs that the job seekerpreviously applied for, along with previously saved personalpreferences. If the job seeker 108 wishes to change preferences, such asranking settings, he/she may be presented with a display screen 1700 inwhich the previously saved settings may be modified as described above.

If previously applied for jobs are found, control then transfers tooperation 1408 where the system 1300 searches and matches available jobsin module 1302 as described above with reference to FIG. 3, and thendisplays the matching results to the job seeker 1402, on a screen 1600such as is shown in FIG. 16 after applying any prior negative filtrationselections.

Screen 1600 displays featured job results 1604, based on previouslydefined job searches as shown by boxes checked in the last search 1602.The results 1604 are shown based on prior ranking parameters as shown onscreen 1700 in FIG. 17. In the screen 1600, an opportunity is providedfor the job seeker to rate the jobs presented on a scale of 1-5,indicated by stars 1606. In addition, on screen 1600, the job seeker canlook at similar jobs by clicking on “similar jobs that may interest you”1608. If the job seeker clicks on this icon 1608, a listing of similarjobs 1500 appears as is shown in FIG. 15. The job seeker 1402 can thenapply a negative filter for subsequent searches by clicking on “Don'tsuggest this job again” 1502. This applies a negative filter into theuser activity monitor module 1314 and the affinity module 1312.

Control then transfers to operation 1414 where the system 1300 permitsthe job seeker 1402 to choose to apply for a newly displayed job. If thejob seeker chooses not to apply for one of the displayed jobs, controltransfers to query operation 1410. On the other hand, if the userchooses to apply for one of the jobs, the apply history for the jobseeker 1402 is updated in the user activity monitoring module 1314, andcontrol transfers to operation 1416.

In operation 1416, since the job seeker has now applied for one of thedisplayed jobs, a new search and matching operation, through thesequence 300 shown in FIG. 3, is performed with the updated applyhistory and click-through information provided as a result of the jobseeker's actions. The results of this match are displayed asrecommendations to the job seeker 1402 as shown in FIG. 16. Control thenreturns to query operation 1414. Again, the job seeker 1402 is given theopportunity to apply for one of the newly displayed jobs and, if he/shedoes so, control again passes to operation 1416, the matching searchsequence 300 repeats, and then back to query operation 1414. Thisiterative process repeats until the job seeker chooses not to apply forone of the displayed jobs, at which point control transfers to operation1420. In operation 1420, the query is made whether the job seeker ratedone or more of the jobs displayed. If so, control transfers to operation1418, where new jobs are recommended based on this new information.Control then transfers to query operation 1419.

In operation 1419, the query is made whether the job seeker 1402 haschanged ranking criteria for searching jobs. if not, control transfersback to operation 1414. If the job seeker 1402 has changed criteria,then control transfers to operation 1422.

In operation 1422, new jobs are presented based on rating and/or rankingchanges. Control then transfers again to operation 1414 where the systemawaits the job seeker to apply for a job, change a rating, or ask forsimilar results as described above. If no jobs are re-rated by the jobseeker 1402 in operation 1420, control transfers back to operation 1410.

When control transfers to query operation 1410, either from operation1420 as just described, or initially from query operation 1406, the jobseeker 1402 is permitted to conduct a new search for jobs. In this case,perhaps the job seeker can provide different input parameters for thejob search desired, such as a different location, title, etc. If such anew search is requested, control transfers to operation 1412 where thesearch is conducted and matching results are displayed as potentialjobs, including elimination of jobs for which a negative response hasbeen provided. Control then passes to query operation 1414 as abovedescribed.

On the other hand, if the job seeker 1402 does not want to performanother job search at this time, the job seeker's job profile 206 isupdated and stored, and control passes to end operation 1432.

The next time the job seeker 1402 logs into the system 1300, the abovedescribed process again begins, but this time with updated informationin the job seeker's profile 206 based on his/her prior actions,preferences set, the previously applied for jobs and correlationsdetermined in the affinity module 1312 described above. In this way, thesystem 1300, as well as is the case with each of the systems explainedabove, continually updates itself and is continually refined, both bythe user's preferences, and by the user's actions. In addition, thesystem 1300 is continually updated based on other user's activitiesimpact the affinity module, such that the system 1300 remains a dynamicsystem responsive to both the user and other user input. In this way thesystem 1300 is constantly changing and being updated such that the userperceives a dynamic job search system that keeps abreast of changes inthe job marketplace as it is being utilized.

The embodiments described above are exemplary and are not to be taken aslimiting in any way. They are merely illustrative of the principles ofthe disclosure. Various changes, modifications and alternatives will beapparent to one skilled in the art Accordingly, it is intended that theart disclosed shall be limited only to the extent required by theappended claims and the rules and principles of applicable law.

1. A system comprising: a plurality of processors; a database comprisingdata related to a plurality of job seekers and/or a plurality of jobs; amatching module implemented on one of the plurality of processors incommunication with the database, the matching module producing jobmatching results by matching one of the job seekers to a potential jobthrough finding one or more common parameters between job seekerparameters associated with the one job seeker and one or more jobparameters associated with the potential job; an individualized datacollection module determining job seeker characteristics based onindividualized information captured from a user interface instantiatedon a job seeker's individual device, wherein the determined job seekercharacteristics are incorporated into job seeker parameters utilized bythe matching module; and a correlation module implemented on one of theplurality of processors in communication with the matching module, thecorrelation module determining a correlation between one of the commonparameters and one or more alternative jobs from the plurality of jobsin part based on tracked behavior characteristics of prior interactionswith the system for each job seeker, wherein the correlation modulecomprises a filtration module generating and storing a negativefiltration indication associated with a job excluding the job in the jobmatching results and the correlated one or more alternative jobsresponsive to a job seeker input negative indication related to theexcluded job, and wherein the correlation module further comprises anaffinity engine configured to determine affinity metrics between thepotential job identified in the job matching results and other jobsinteracted with by the plurality of job seekers and to determinealternative jobs to the job matching results based on the determinedaffinity metrics.
 2. The system according to claim 1 wherein thematching module determines a matching score for each of the commonparameters between the job seeker and the one or more jobs.
 3. Thesystem according to claim 1 wherein the filtration module queries thejob seeker for at least one reason for excluding the job similar to oneor more of the plurality of jobs.
 4. The system according to claim 3wherein the correlation module considers the at least one reason indetermining subsequent matching suggestion jobs.
 5. The system accordingto claim 2 wherein suggestion jobs made available of download anddisplay to the job seeker are ranked according to the matching scores.6. A processor-implemented method comprising: building a job seekerprofile of job seeker parameters in response to job seeker input;determining job seeker characteristics based on individualizedinformation captured from a user interface instantiated on a jobseeker's individual device, wherein the determined job seekercharacteristics are incorporated into the job seeker parameters; inresponse to a job seeker query received over a network, producing jobmatching results by matching the job seeker to one or more potentialjobs through finding one or more common parameters between job seekerparameters associated with the job seeker and job description parametersassociated with the one or more potential jobs in part based on trackedbehavior characteristics of prior queries for the job seeker;determining affinity metrics between the potential jobs identified inthe job matching results and other jobs applied by the plurality of jobseekers; determining alternative jobs to the job matching results basedon the determined affinity metrics and based on the evaluative ratingprovided by the job seeker; providing the matching results and thealternative jobs for consideration by the job seeker over the network tothe job seeker; querying the job seeker over the network whether or notto filter one of the potential jobs from subsequent matching results;and generating via a processor, and storing in a data storage element, anegative filtration indication associated with a job for excluding thejob in the job matching results and the determined alternative jobsresponsive to a job seeker input negative indication related to theexcluded job.
 7. The method according to claim 6 further comprisingdetermining a matching score for each of the common parameters betweenthe job seeker and the identified potential jobs.
 8. The methodaccording to claim 6 further comprising determining an affinityrelevance value for each alternative job based on a popularity of thealternative job.
 9. The method according to claim 8 further comprisingranking the alternative jobs according to the affinity relevance value.10. The method according to claim 6 further comprising: if the jobseeker responds to the query by asking not to display the one of thepotential jobs, then removing the one potential job from subsequentmatching results.
 11. The method according to claim 10 furthercomprising removing the one potential job from the affinity determiningoperation.
 12. The method according to claim 11 wherein if the jobseeker asks not to display one or more of the potential jobs, queryingthe job seeker for a reason selected from a plurality of predeterminednegative reasons.
 13. The method according to claim 12 furthercomprising applying the reason to remove similar potential jobs fromrecommendations in the determining operation.
 14. A method comprising:storing, by a computing system, one or more job seeker parameters inresponse to job seeker input by each of a plurality of job seekers;storing, by the computing system, job parameters in response to inputover a network by an employer/recruiter for each of one or more jobs;determining job seeker characteristics based on individualizedinformation captured from a user interface instantiated on a jobseeker's individual device, wherein the determined job seekercharacteristics are incorporated into the job seeker parameters; inresponse to a query from one of the job seekers received over thenetwork, finding, by the computing system, one or more common parametersbetween the one job seeker's parameters and the stored job parameters toproduce matching job results; correlating, by the computing system, oneor more matching job parameters in the matching job results with otherjobs based on the stored other job seeker parameters in part based ontracked behavior characteristics of prior interactions with thecomputing system for each job seeker; determining affinity metricsbetween jobs in the matching job results and other jobs applied by theplurality of job seekers; determining and displaying, by the computingsystem, alternative jobs to the matching jobs from the correlation dataand the determined affinity metrics; if the job seeker requests removalof one or more suggested alternative jobs, then querying, by thecomputing system the job seeker for a reason for removal from a set ofpredetermined reasons; receiving, by the computing system, the reason;and generating and storing a negative filtration indication includingthe received reason associated with the one or more removed jobs forexcluding the one or more removed jobs in the job matching results andthe determined alternative jobs responsive to a job seeker inputnegative indication related to the excluded job.
 15. The methodaccording to claim 14 further comprising transmitting the alternativejobs for display to the one job seeker.
 16. The method according toclaim 14 further comprising repeating the storing, finding, correlating,determining and querying operations if the one job seeker applies forone of the displayed alternative jobs.
 17. The method according to claim14 wherein the other job seeker parameters include jobs that the otherjob seekers applied for.
 18. A system comprising: means for storing in amemory job seeker parameters in response to job seeker input by each ofa plurality of job seekers; means for storing in the memory jobparameters in response to input by an employer/recruiter for each of oneor more jobs; means for determining job seeker characteristics based onindividualized information captured from a user interface instantiatedon a job seeker's individual device, wherein the determined job seekercharacteristics are incorporated into the job seeker parameters; meansfor, in response to a query from one of the job seekers received over anetwork, finding one or more common parameters between the one jobseeker's parameters and the stored job parameters to produce jobmatching results comprising matching jobs in part based on trackedbehavior characteristics of prior interactions with the system for eachjob seeker; means for correlating between one or more matching jobparameters and the stored job seeker parameters of one or more of theother job seekers to produce alternative jobs; means for determiningaffinity metrics between the potential jobs identified in the jobmatching results and other jobs applied by the plurality of job seekers;means for determining alternative jobs based on the determined affinitymetrics and correlation; means for querying the one job seeker over thenetwork on a display of a computing device of matching and alternativejobs whether to remove at least one of the matching jobs or alternativejobs; and means for updating the matching results and the alternativejobs for consideration by the one job seeker including generating andstoring a negative filtration indication associated with a job forexcluding the job in the job matching results and the producedalternative jobs responsive to a job seeker input negative indicationrelated to the excluded job.
 19. The system according to claim 18further comprising means for determining a relevance value of thealternative jobs to the matching jobs.
 20. The system according to claim18 wherein the means for correlating comprises an affinity module thatdetermines affinities based on jobs applied for data for each of theplurality of job seekers.
 21. A system comprising: a plurality ofprocessors; a database; a matching module implemented on one of theplurality of processors connected to the database and to a web serveraccessible to a job seeker, said matching module determining a matchedjob for the job seeker by comparing job parameters and job seekerparameters; an individualized data collection module determining jobseeker characteristics based on individualized information captured froma user interface instantiated on a job seeker's individual device,wherein the determined job seeker characteristics are incorporated intojob seeker parameters utilized by the matching module; a correlationmodule implemented on one of the plurality of processors communicatingwith the job matching module and the database, the correlation modulecomprising: a user activity monitor module implemented on one of theplurality of processors tracking job seeker activity within the systemfor matching job seekers with potential jobs based on behavior of prioractivity for the job seeker; an affinity module implemented on one ofthe plurality of processors configured to determine affinity metricsbetween the matched job and other jobs interacted with by other jobseekers based on the tracked job seeker activity and determinealternative jobs in addition to the matched job for the job seeker basedon the determined affinity metrics; and a filtration module implementedon one of the plurality of processors operably coupled to the affinitymodule and user activity monitor module receiving preferences from a jobseeker to refine correlations made by the matching module andcorrelation module for consideration by the job seeker, and generatingand storing a negative filtration indication associated with a job forexcluding the job in instant and subsequent job queries for the jobseeker.
 22. The system according to claim 21 wherein the filtrationmodule presents to the job seeker an option to select a matching job tobe eliminated from subsequent display to the job seeker.
 23. The systemaccording to claim 21 wherein the filtration module communicates withthe user activity monitor module to ensure subsequent matching resultsdo not include a matching job selected by the job seeker forelimination.
 24. The system according to claim 22 wherein the filtrationmodule queries the job seeker for one or more reasons for eliminationupon selection by the job seeker of a matching job to be eliminated. 25.The system according to claim 24 wherein the one or more reasons areselected from a predetermined set of reasons displayed to the job seekerfor selection.
 26. An intelligent job matching system, comprising: amemory; a processor disposed in communication with said memory, andconfigured to issue a plurality of processing instructions stored in thememory, wherein the processor issues instructions to: retrieve a jobseeker profile including a plurality of job seeker parameters and a listof job profiles, each job profile including a plurality of jobdescription parameters; determine job seeker characteristics based onindividualized information captured from a user interface instantiatedon a job seeker's individual device, wherein the determined job seekercharacteristics are incorporated into the plurality of job seekerparameters; determine a matched job from the list of job profiles bycomparing the plurality of job seeker parameters with the plurality ofjob description parameters of each job profile, the matched job and thejob seeker profile having a common parameter; determine affinity metricsbetween the matched job and other jobs interacted with by other jobseekers based on prior job applying activity data; determine analternative job for the job seeker by correlating the alternative jobwith the matched job based on the determined affinity metrics, whereinthe prior job applying activity data indicates the alternative job andthe matched job have been applied for by a same job seeker; present thedetermined matched job and the alternative job to the job seeker via auser interface; receive a negative election of at least one of thepresented jobs from the job seeker via the user interface; and generateand store a negative filtration indication associated with the at leastone negatively elected job for excluding the negatively elected job fromany instant and subsequent job matches for the job seeker.